AWS Machine Learning Blog
Category: Amazon Lex
Transform one-on-one customer interactions: Build speech-capable order processing agents with AWS and generative AI
In today’s landscape of one-on-one customer interactions for placing orders, the prevailing practice continues to rely on human attendants, even in settings like drive-thru coffee shops and fast-food establishments. This traditional approach poses several challenges: it heavily depends on manual processes, struggles to efficiently scale with increasing customer demands, introduces the potential for human errors, […]
Expedite your Genesys Cloud Amazon Lex bot design with the Amazon Lex automated chatbot designer
The rise of artificial intelligence (AI) has created opportunities to improve the customer experience in the contact center space. Machine learning (ML) technologies continually improve and power the contact center customer experience by providing solutions for capabilities like self-service bots, live call analytics, and post-call analytics. Self-service bots integrated with your call center can help […]
Enhance Amazon Connect and Lex with generative AI capabilities
Effective self-service options are becoming increasingly critical for contact centers, but implementing them well presents unique challenges. Amazon Lex provides your Amazon Connect contact center with chatbot functionalities such as automatic speech recognition (ASR) and natural language understanding (NLU) capabilities through voice and text channels. The bot takes natural language speech or text input, recognizes […]
Integrate QnABot on AWS with ServiceNow
Do your employees wait for hours on the telephone to open an IT ticket? Do they wait for an agent to triage an issue, which sometimes only requires restarting the computer? Providing excellent IT support is crucial for any organization, but legacy systems have relied heavily on human agents being available to intake reports and […]
Build generative AI agents with Amazon Bedrock, Amazon DynamoDB, Amazon Kendra, Amazon Lex, and LangChain
Generative AI agents are capable of producing human-like responses and engaging in natural language conversations by orchestrating a chain of calls to foundation models (FMs) and other augmenting tools based on user input. Instead of only fulfilling predefined intents through a static decision tree, agents are autonomous within the context of their suite of available […]
Elevate your self-service assistants with new generative AI features in Amazon Lex
In this post, we talk about how generative AI is changing the conversational AI industry by providing new customer and bot builder experiences, and the new features in Amazon Lex that take advantage of these advances. As the demand for conversational AI continues to grow, developers are seeking ways to enhance their chatbots with human-like […]
Deploy generative AI self-service question answering using the QnABot on AWS solution powered by Amazon Lex with Amazon Kendra, and Amazon Bedrock
Powered by Amazon Lex, the QnABot on AWS solution is an open-source, multi-channel, multi-language conversational chatbot. QnABot allows you to quickly deploy self-service conversational AI into your contact center, websites, and social media channels, reducing costs, shortening hold times, and improving customer experience and brand sentiment. In this post, we introduce the new Generative AI features for QnABot and walk through a tutorial to create, deploy, and customize QnABot to use these features. We also discuss some relevant use cases.
Enhance Amazon Lex with conversational FAQ features using LLMs
Amazon Lex is a service that allows you to quickly and easily build conversational bots (“chatbots”), virtual agents, and interactive voice response (IVR) systems for applications such as Amazon Connect. Artificial intelligence (AI) and machine learning (ML) have been a focus for Amazon for over 20 years, and many of the capabilities that customers use […]
Enhance Amazon Lex with LLMs and improve the FAQ experience using URL ingestion
In today’s digital world, most consumers would rather find answers to their customer service questions on their own rather than taking the time to reach out to businesses and/or service providers. This blog post explores an innovative solution to build a question and answer chatbot in Amazon Lex that uses existing FAQs from your website. […]
Exploring Generative AI in conversational experiences: An Introduction with Amazon Lex, Langchain, and SageMaker Jumpstart
Customers expect quick and efficient service from businesses in today’s fast-paced world. But providing excellent customer service can be significantly challenging when the volume of inquiries outpaces the human resources employed to address them. However, businesses can meet this challenge while providing personalized and efficient customer service with the advancements in generative artificial intelligence (generative […]